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CNNs for automatic glaucoma assessment using fundus images: an extensive validation
BACKGROUND: Most current algorithms for automatic glaucoma assessment using fundus images rely on handcrafted features based on segmentation, which are affected by the performance of the chosen segmentation method and the extracted features. Among other characteristics, convolutional neural networks...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425593/ https://www.ncbi.nlm.nih.gov/pubmed/30894178 http://dx.doi.org/10.1186/s12938-019-0649-y |